Detecting Spam at the Network Level

Anna Sperotto, G. Vliek, R. Sadre, Aiko Pras

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    10 Citations (Scopus)
    90 Downloads (Pure)

    Abstract

    Spam is increasingly a core problem affecting network security and performance. Indeed, it has been estimated that 80% of all email messages are spam. Content-based filters are a commonly deployed countermeasure, but the current research focus is now moving towards the early detection of spamming hosts. This paper investigates if spammers can be detected at the network level, based on just flow data. This problem is challenging, since no information about the content of the email message is available. In this paper we propose a spam detection algorithm, which is able to discriminate between benign and malicious hosts with 92% accuracy.
    Original languageUndefined
    Title of host publicationProceedings of the 15th Open European Summer School and IFIP TC6.6 Workshop, EUNICE 2009
    Place of PublicationBerlin
    PublisherSpringer
    Pages208-216
    Number of pages9
    ISBN (Print)978-3-642-03699-6
    DOIs
    Publication statusPublished - 26 Aug 2009
    Event15th Open European Summer School and IFIP TC6.6 Workshop 2009 - Barcelona, Spain
    Duration: 7 Sep 20099 Sep 2009
    Conference number: 15
    http://www.nets.upf.edu/pages/eunice09/

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer Verlag
    Volume5733
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Workshop

    Workshop15th Open European Summer School and IFIP TC6.6 Workshop 2009
    Abbreviated titleEUNICE 2009
    CountrySpain
    CityBarcelona
    Period7/09/099/09/09
    Internet address

    Keywords

    • IR-67583
    • EWI-16007
    • METIS-263998

    Cite this